Altair: Interactive Statistical Visualizations for Python

Vanderplas, Jake; Granger, Brian; Heer, Jeffrey; Moritz, Dominik; Wongsuphasawat, Kanit; Satyanarayan, Arvind; Lees, Eitan; Timofeev, Ilia; Welsh, Ben; Sievert, Scott

doi:10.21105/joss.01057

Cited by 200 publications

(124 citation statements)

References 7 publications

Supporting

Mentioning

124

Contrasting

Order By: Relevance

“…These analyses are carried out in Python (Python Software Foundation 2019), its scientific ecosystem (Perez & Granger 2007;Kluyver et al 2016;van der Walt et al 2011;McKinney 2010;Hunter 2007;Kibirige 2019;Waskom 2018;Roubeyrie & Celles 2018;VanderPlas et al 2018;Pedregosa et al 2011;Jones et al 2001) and R (R Core Team 2019).…”

Section: Discussionmentioning

confidence: 99%

The importance of thermal modelling and prototyping in shelter design

Fosas

Moran

Natarajan

et al. 2019

Building Research & Information

View full text Add to dashboard Cite

More than 9 million people live in shelters globally, often in extremely hot climates. The thermal performance of shelters is often overlooked in the design process, despite being a consideration second only to safety in surveys of camp dwellers. Indeed, indoor temperatures exceeding 40 °C have been recorded in previous studies. To aid in improving conditions, the roles building simulation and prototyping could play in forecasting shelter thermal performance as part of a new shelter design process are examined. The thermal performance of prototypes, built in the refugee camp of Azraq, was monitored during the hot season to evaluate four design approaches: (1) "blind" (uncalibrated) models, (2) calibrated models, (3) on-site design-variants and (4) off-site prototypes. These included the original shelter and six design alternatives implementing different overheating countermeasures. The results demonstrate that blind models are sensitive to the judgement of uncertainties but were still qualitatively useful. Model calibration vastly improves the agreement and significantly enhances forecasts of performance for the design alternatives, which remained similar across examined climates. It is therefore concluded that simulation and prototyping, either on-site or off-site, should be adopted within the shelter design process before mass deployment, to create better living conditions for their dwellers.

show abstract

Section: Discussionmentioning

confidence: 99%

The importance of thermal modelling and prototyping in shelter design

Fosas

Moran

Natarajan

et al. 2019

Building Research & Information

View full text Add to dashboard Cite

show abstract

“…spectrum_utils is available for Python 3.6+ and can be easily installed via conda using the Bioconda channel [8]. spectrum_utils depends on Numpy [23] and Numba [11] for efficient numerical computation, Pyteomics [7,12] for peptide fragment ion mass calculations, RDKit [18] for SMILES string handling, matplotlib [9] for static plotting, and Altair [24] and Pandas [15] for interactive plotting.…”

Section: Code Availabilitymentioning

confidence: 99%

spectrum_utils: A Python package for mass spectrometry data processing and visualization

Bittremieux

2019

Preprint

View full text Add to dashboard Cite

Given the wide diversity in applications of biological mass spectrometry, custom data analyses are often needed to fully interpret the results of an experiment. Such bioinformatics scripts necessarily include similar basic functionality to read mass spectral data from standard file formats, process it, and visualize it. Rather than having to reimplement this functionality, to facilitate this task, spectrum_utils is a Python package for mass spectrometry data processing and visualization. Its high-level functionality enables developers to quickly prototype ideas for computational mass spectrometry projects in only a few lines of code. Notably, the data processing functionality is highly optimized for computational efficiency to be able to deal with the large volumes of data that are generated during mass spectrometry experiments. The visualization functionality makes it possible to easily produce publication-quality figures as well as interactive spectrum plots for inclusion on web pages. spectrum_utils is available for Python 3.6+, includes extensive online documentation and examples, and can be easily installed using conda. It is freely available as open source under the Apache 2.0 license at https: //github.com/bittremieux/spectrum_utils.

show abstract

“…For the downstream analysis we used the current genome annotation Araport 11 [72]. The complete pipeline was implemented in Snakemake [73], mainly using the scientific python stack [74,75,76,77], R visualization libraries [78,79,36], and tools for genome analysis [38,80,81]. Further details are given in the Supplementary Section S1.2.…”

Section: Data Processingmentioning

confidence: 99%

Cell Type-specific Genome Scans of DNA Methylation Diversity Indicate an Important Role for Transposable Elements

Kartal

Schmid

Grossniklaus

2019

Preprint

View full text Add to dashboard Cite

The epigenome modulates the activity of genes and supports the stability of the genome. The epigenome can also contain phenotypically relevant, heritable marks that may vary at the organismic and population level. Such non-genetic standing variation may be relevant to ecological and evolutionary processes. To identify loci susceptible to selection, it is common to profile large populations at the genome scale, yet methods to perform such scans for epigenetic diversity are barely tapped. Here, we develop a scalable, information-theoretic approach to assess epigenome diversity based on Jensen-Shannon divergence (JSD) and demonstrate its practicality by measuring cell type-specific methylation diversity in the model plant Arabidopsis thaliana. DNA methylation diversity tends to be increased in the CG as compared to the non-CG (CHG and CHH) sequence context but the tissue or cell type has an impact on diversity at non-CG sites. Less accessible, more heterochromatic states of chromatin exhibit increased diversity. Genes tend to carry more single-methylation polymorphisms when they harbor gene body-like chromatin signatures and flank transposable elements (TEs). In conclusion, the analysis of DNA methylation with JSD in Arabidopsis demonstrates that the genomic location of a gene dominates its methylation diversity, in particular the proximity to TEs which are increasingly viewed as drivers of evolution. Importantly, the JSD-based approach we implemented here is applicable to any population-level epigenomic data set to analyze variation in epigenetic marks among individuals, tissues, or cells of any organism, including the epigenetic heterogeneity of cells in healthy or diseased organs such as tumors.

show abstract

Altair: Interactive Statistical Visualizations for Python

Cited by 200 publications

References 7 publications

The importance of thermal modelling and prototyping in shelter design

The importance of thermal modelling and prototyping in shelter design

spectrum_utils: A Python package for mass spectrometry data processing and visualization

Cell Type-specific Genome Scans of DNA Methylation Diversity Indicate an Important Role for Transposable Elements

Contact Info

Product

Resources

About